Study Shows Potential New Way to Detect Autism: SPECT Scans Can Be the Key
Autism Accurately Diagnosed with Brain SPECT Imaging
Brain Blood Flow Shows Pattern Consistent with Autism
COSTA MESA, CA: The diagnosis of Autism Spectrum Disorder (ASD) relies on history and behavioral observation, lacking reliable biomarkers. Researchers from Amen Clinics and the University of Southern California performed what is believed to be the largest ever analysis of brain SPECT (single photon emission computed tomography) scans, a nuclear medicine study that evaluates blood flow and activity patterns, on 928 persons with ASD obtained 9 different sites to investigate whether these scans distinguish ASD from healthy controls. The age range of patients were from 13-67 years.
Using sophisticated machine learning algorithms, high levels of separation were obtained. The areas the most predicted ASD were found in the cerebellum, anterior cingulate gyrus, amygdala, frontal and temporal lobes.
Lead author Daniel Amen, MD, child psychiatrist and founder of Amen Clinics said, “Currently, the diagnosis of ASD includes a clinical history, mental status examination and structured screening tools, leaving clinicians in the dark as to the underlying physiology. At Amen Clinics, we frequently see increased activity in the anterior cingulate, leading to obsessive behavior, and decreases in the temporal lobes and cerebellum, which are often associated with learning issues. Having SPECT scans on ASD patients has helped us better target treatment.”
This is the first brain SPECT imaging study demonstrating the use of machine learning methods to predict ASD from a healthy control (HC). These results add to the growing body of literature validating the use of machine learning approaches with functional neuroimaging data to improve prediction and classification of individuals with psychiatric disorders like autism. Given the heterogeneity of ASD, this approach has important implications in the clinical setting in both the diagnosis, intervention and monitoring of treatment outcomes.
Due to the variability of the underlying brain function problems in ASD and the complicating factor of a high rate of co-existing disorders, SPECT brain imaging is extremely useful for revealing otherwise hidden information. This helps us select the best course of treatment for each person with the disorder.
ASD is a multi-faceted and misunderstood condition; Amen Clinics can help decipher the right treatments and protocols. If you would like to learn more, please visit us online or call 888-288-9834 today.
Amen DG (2017) Functional SPECT neuroimaging using machine learning algorithms distinguishes autism spectrum disorder from healthy subjects. J Syst Integr Neurosci 3: doi:10.15761/JSIN.1000160
Published: April 10, 2017